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Artificial Intelligence (AI) is becoming essential in modern organizations, significantly enhancing innovation, efficiency, and competitive advantage. By mimicking human intelligence, AI not only automates mundane tasks but also improves decision-making through advanced data analysis and promotes innovation in products and services. This study aims to map the existing research landscape, identify prevalent trends, and understand the factors driving widespread AI adoption. This bibliometric analysis is crucial as it outlines the current state and evolution of AI implementation in both academic and practical contexts. It highlights key trends and research gaps, aiding scholars and industry professionals in making informed decisions about AI deployment and guiding future research directions. Employing bibliometric methods with VOSviewer software and data from the Web of Science (WoS) database. The results show a significant increase in AI-related publications. This underscores a growing global interest and engagement in AI.

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Innovation Through Intelligence: Mapping the Adoption of Artificial Intelligence with Bibliometric Methods

  • 章节

  • 发表日期：

    2025年

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  • Sulieman Ibraheem Mohammad,
  • Ala’a M. Al-Momani,
  • Asokan Vasudevan,
  • Mousa Masadeh,
  • Aktham Al sarayreh,
  • Khaldoon Jahmani,
  • Rania Ibrahim Mohammad,
  • Anber Abraheem Shlash Mohammad,
  • Rana Ibrahim Mohammad

摘要

Artificial Intelligence (AI) is becoming essential in modern organizations, significantly enhancing innovation, efficiency, and competitive advantage. By mimicking human intelligence, AI not only automates mundane tasks but also improves decision-making through advanced data analysis and promotes innovation in products and services. This study aims to map the existing research landscape, identify prevalent trends, and understand the factors driving widespread AI adoption. This bibliometric analysis is crucial as it outlines the current state and evolution of AI implementation in both academic and practical contexts. It highlights key trends and research gaps, aiding scholars and industry professionals in making informed decisions about AI deployment and guiding future research directions. Employing bibliometric methods with VOSviewer software and data from the Web of Science (WoS) database. The results show a significant increase in AI-related publications. This underscores a growing global interest and engagement in AI.